A/B testing is a term commonly used in web development, online marketing, and other forms of advertising to describe simple randomized experiments with two variants, namely A and B, which are the control and treatment in the controlled experiment. A/B testing may also be referred to as randomized controlled experiments, online controlled experiments, and split testing. In web design (especially user experience design), the goal is to identify changes to webpages that increase or maximize an outcome of interest (e.g., click-through rate for a banner advertisement). As the name implies, two versions (A and B) of webpage configurations are compared, which are identical except for one variation that may impact a user's behavior. Version A may be the currently used version (referred to as control), while Version B is modified in some respect (referred to as treatment). For instance, on an e-commerce website the purchase funnel is typically a good candidate for A/B testing, as even marginal improvements in drop-off rates can represent a significant gain in sales. Significant improvements can sometimes be seen through variation in text, layout, image, colors, or other aspects of the webpage configuration. The multivariate or multinomial testing is similar to A/B testing, but may test more than two different versions at the same time and/or has more controls, etc.